A very important and challenging problem in the design of high-speed communication networks is that of providing Quality of Service (QoS) guarantees, usually specified in terms of loss probabilities or packet delays in the network. For example, the control of packet delays is often of crucial importance, particularly for real-time applications such as video delivery systems, wireless networks, multimedia networks, call centers, etc. A basic decision that has to be made in such contexts is that of connection admission control, i.e., one has to determine when a new user can be admitted to the system, while still fulfilling the QoS requirements of all users already in the system. Moreover, users already in the system have to be scheduled in the most efficient manner so as to maximize the number of users that can be admitted into the system. Unfortunately, conventional scheduling techniques are unable to provide adequate QoS guarantees.
A number of these conventional scheduling techniques are based on deterministic QoS guarantees, as opposed to probabilistic guarantees. For example, in L. Georgiadis, R. Guerin and A. Parekh, “Optimal multiplexing on a single link: delay and buffer requirements,” IEEE Transactions on Information Theory, 43(5):1518–1535, 1997, and J. Liebeherr, D. Wrege, and D. Ferrari, “Exact admission control for networks with a bounded delay service,” IEEE/ACM Transactions on Networking, 4(6):885–901, 1996, it has been shown that an Earliest Deadline First (EDF) scheduling technique is optimal in the context of providing deterministic QoS guarantees for a single node of a communication network. Another known technique, Coordinated EDF (CEDF), described in M. Andrews, L. Zhang, “Minimizing End-to-End Delay in High-Speed Networks with a Simple Coordinated Schedule,” IEEE INFOCOM'99, pp. 380–388, 1999, uses randomness to spread out packet transmission deadlines.
It is generally believed that deterministic QoS requirements such as those associated with the above-noted conventional scheduling techniques can lead to an overly conservative admission policy, and a consequent decrease in system throughput. In contrast, probabilistic QoS requirements usually provide the very advantageous trade off of a small amount of QoS for a large capacity gain. A need therefore exists for improved scheduling techniques that can meet probabilistic QoS requirements.